Abstract 704: Development of a patient-derived xenograft (PDX) modeling program to enable pediatric precision medicine
Authors: Filemon S. Dela Cruz, Joseph G. McCarter, Daoqi You, Nancy Bouvier, Xinyi Wang, Kristina C. Guillan, Armaan H. Siddiquee, Katie B. Souto, Hongyan Li, Teng Gao, Dominik Glodzik, Daniel Diolaiti, Neerav N. Shukla, Joachim Silber, Umeshkumar K. Bhanot, Faruk Erdem Kombak, Diego F. Coutinho, Shanita Li, Juan E. Arango Ossa, Juan S. Medina-Martinez, Michael V. Ortiz, Emily K. Slotkin, Michael D. Kinnaman, Sameer F. Sait, Tara J. O'Donohue, Marissa Mattar, Maximiliano Meneses, Michael P. LaQuaglia, Todd E. Heaton, Justin T. Gerstle, Nicola Fabbri, Chelsey M. Burke, Irene M. Rodriquez-Sanchez, Christine A. Iacobuzio-Donahue, Julia L. Glade Bender, Ryan D. Roberts, Jason T. Yustein, Nino C. Rainusso, Brian D. Crompton, Elizabeth Stewart, Alejandro Sweet-Cordero, Leanne C. Sayles, Andrika D. Thomas, Michael H. Roehrl, Elisa de Stanchina, Elli Papaemmanuil, Andrew L. Kung
Journal: Cancer Research (2022)

Abstract Background: Recapitulation of the full spectrum of genomic changes driving patient tumors have resulted in increased use of patient-derived xenograft (PDX) models in studies of basic cancer biology and preclinical drug development. Given the translational potential of PDXs and limited availability of pediatric cancer models, we established a PDX program to expand the existing collection of pediatric PDXs in the community and enable pre- and post-clinical studies. Methods: PDX generation requests were integrated into clinical workflows to maximize identification of eligible patients for informed consent and tissue collection at Memorial Sloan Kettering Cancer Center. Methodologies for tissue procurement and cryopreservation were optimized to facilitate implantation into host immunodeficient mice and enable multi-institutional tissue exchange for model building. A bioinformatics pipeline was established to allow molecular validation of engrafted PDXs using a next-generation targeted gene panel (MSK-IMPACT) evaluating concordance based on acquired mutations, copy number alterations and clonal structure. Results: Between November 2016 - October 2021, 379 PDX models were developed (265 distinct models) representing 69 discrete diagnoses. Sarcoma represents the most common model type (50 discrete osteosarcoma, 20 desmoplastic small round cell tumor, 14 Ewing sarcoma, 24 rhabdomyosarcoma, 2 CIC/DUX4 and 2 BCOR-rearranged sarcoma) followed by neuroblastoma (n=35), leukemia (n=44), and Wilms tumor (n=15). While the majority of PDXs were established from recurrent or metastatic tissue, 7 paired diagnostic/pre-therapy and post-therapy or relapse models were generated. Genomic characterization of PDXs demonstrate excellent concordance and recapitulation of single nucleotide variants (90%), structural (88%) and copy number variants (94%) between patient tumor and matched PDX. Discrepancies between matched patient/PDX pairs are due to sub-clonal heterogeneity in source tumors with clonal outgrowth in the PDX. Analysis of serial PDX passages also demonstrate stable recapitulation of the genomic profile. Establishment of a diverse PDX collection allowed preclinical evaluation of 10 targeted agents across a spectrum of pediatric tumors and provided the preclinical rationale for 3 investigator-initiated pediatric clinical trials. Conclusions: Investment in the development of a phenotypically diverse and biologically faithful collection of pediatric PDX models enables the goals of precision medicine. Optimization of PDX workflows and methods has also enabled the development of a pediatric PDX consortium (PROXC - Pediatric Research in Oncology Xenografting Consortium) to further support the development of pre- and post-clinical studies for pediatric cancer. Citation Format: Filemon S. Dela Cruz, Joseph G. McCarter, Daoqi You, Nancy Bouvier, Xinyi Wang, Kristina C. Guillan, Armaan H. Siddiquee, Katie B. Souto, Hongyan Li, Teng Gao, Dominik Glodzik, Daniel Diolaiti, Neerav N. Shukla, Joachim Silber, Umeshkumar K. Bhanot, Faruk Erdem Kombak, Diego F. Coutinho, Shanita Li, Juan E. Arango Ossa, Juan S. Medina-Martinez, Michael V. Ortiz, Emily K. Slotkin, Michael D. Kinnaman, Sameer F. Sait, Tara J. O'Donohue, Marissa Mattar, Maximiliano Meneses, Michael P. LaQuaglia, Todd E. Heaton, Justin T. Gerstle, Nicola Fabbri, Chelsey M. Burke, Irene M. Rodriquez-Sanchez, Christine A. Iacobuzio-Donahue, Julia L. Glade Bender, Ryan D. Roberts, Jason T. Yustein, Nino C. Rainusso, Brian D. Crompton, Elizabeth Stewart, Alejandro Sweet-Cordero, Leanne C. Sayles, Andrika D. Thomas, Michael H. Roehrl, Elisa de Stanchina, Elli Papaemmanuil, Andrew L. Kung. Development of a patient-derived xenograft (PDX) modeling program to enable pediatric precision medicine [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 704.